International e-benchmarking: flexible peer development of authentic learning principles in higher education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
More and more, social technologies and virtual work methods are facilitating new ways of crossing boundaries in professional development and international collaborations. This paper examines the peer development of higher education teachers through the experiences of the IVBM project (International Virtual Benchmarking, 2009–2010). The e-benchmarking process in which teachers applied authentic learning criteria is described, as are the e-tools (Ning, ACP) and the methods employed collaboratively to develop e-learning competence. Cases came from Finland, Korea, Canada, Belgium and Great Britain. The project formed an international virtual learning community for teachers. In peer development, elements of authentic learning were assigned meaning, development alternatives were considered and the interpretation of authentic learning in different situations and cultures was made concrete. The results promote and inform the planning of e-benchmarking communities and flexible virtual teamwork in professional development and education contexts.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.048 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it